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A Lagrangian study of the contribution of the Canary coastal upwelling to the nitrogen budget of the open North Atlantic
<p>The attached datasets constitute the particle trajectory data produced in the experiment for Hailegeorgis et al..</p> <p>The "traj_upwell_1d_70m_1d-variables.nc" contains variables that describe different aspects of each upwelled particle (mostly regarding a particle's release or its initial or final conditions).</p> <p>The rest of the files with the format "traj_upwell_1d_70m_XXX-traj.nc" describe an attribute XXX (location or nutrient concentration) along the trajectory of upwelled particles tracked as part of the experiment.</p> <p>With ARIANE, particles are released and tracked in a ROMS simulation of the Canary coastal upwelling region. Out of the ~10M particles, the trajectories of the ~353K (~3.6%) that upwell are included. The variable "index_in_full_exp" in file "traj_upwell_1d_70m_1d-variables.nc" shows the index of each of these upwelling particles in the larger pool of released particles. For each upwelled particle, out of the 720-day trajectories starting from its release into the coast, the values from its upwelling step to its exit from the experiment are included, with the values outside this range being filled with a generic value (1.e20). An upwelled particle exits the experiment when it leaves the regional ROMS simulation altogether or when it leaves the coast and returns to the coast to re-upwell (more details in the paper).</p> <p>Be mindful of the different values of time. In "traj_upwell_1d_70m_1d-variables.nc", the variable "release_time" tells each particle's release time, in days since onset of the ROMS simulation, while variable "coast_exit_time" tells each particle's day of exiting coast, in days since its release. In each particle's trajectory (in traj_lon, traj_lat, etc), the first and last steps with valid values are the same as the days of its upwelling and its exit, respectively, since its release.</p> <p>The files contain the name and description of each variable. Along with the details in the publication, the descriptions here should be enough to fully interpret the information and replicate our analysis.</p>
Processing of MODIS-Aqua data with Self-Organizing Maps NeuroVaria method for the southern canary upwelling system
<p>Abstract</p> <p>This ocean color dataset is derived from MODIS_Aqua sensor measurements covering the Southern Canary upwelling system. The raw L1A measurements were downloaded from NASA's Ocean Color web site and then processed using the Ocean Biology Processing Group's (OBPG) Multi-Sensor Level-1 to Level-2 (MSL12) code. The l2gen program, based on its standard process, generates Level-2 parameters consisting of the top of atmosphere radiance, the radiance of each ocean and atmosphere component, the measurement angles, Level-2 flags, ... The top of atmosphere radiance is pre-corrected to keep only a dependence on the diffuse transmittance, the aerosol contribution and the water leaving radiance.</p> <p><br> The pre-corrected product and measurement angles are assimilated using the Self-Organizing Map<br> NeuroVaria (SOM-NV) code (Diouf et al., 2013). SOM-NV is an algorithm based on two statistical models<br> that classify a dataset into a map, and then use the information from that map to deliver atmospheric and oceanic parameters from the satellite observation.</p> <p>The parameters of interest are the remote sensing reflectance spectra (Rrs(λ)) and the aerosol optical thickness (AOT) at 869 nm (aot_869). The Rrs at blue (443 and 488 nm) and green (547 nm) are used to calculate chlorophyll-a concentration from the OBPG OCx algorithm (chl_ocx, O'Reilly et al., 1998; Mobley et al., 2016).</p> <p>These geophysical parameters are projected onto a fixed grid at 1/96° resolution and archived in a daily netcdf format files. Each file contains five visible reflectances Rrs(λ) (with λ = 412, 443, 488, 531, and 547 nm), chl_ocx, aot_869, and latitude and longitude coordinates. These parameters are described in the files, along with the global attributes.</p> <p><br> The netcdf files are formatted as follows: SOM-NV-Ayyyydddhhmmss.nc; where yyyy = year; ddd = Julian<br> day; hh = hour; mm = minute; ss = second. The extension "Ayyyydddhhmmss.nc", corresponds to the name<br> of the MODIS_aqua file of the day. When two input files exist for the same day, within 5 minutes, the two<br> scans are concatenated and the orbit keeps the name of the second file.<br> All files are compressed internally to a size of 4, to facilitate transfers.</p> <p>%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</p> <p>Résumé</p> <p>Ce jeu de données de couleur de l’eau est issu des mesures du capteur MODIS_Aqua sur la partie sud du système d’upwelling des Canaries. Les mesures brutes L1A ont été téléchargées du site Ocean Color de la NASA, puis traitées à l’aide du code de traitement « Multi-Sensor Level-1 to Level-2 (MSL12) » du groupe Ocean Biology Processing Group (OBPG). La version standard du programme l2gen génère les paramètres de niveau 2 constitués de la luminance totale mesurée, de la luminance de chaque composante du système océan-atmosphère, des angles de mesures, des masques de niveau 2, …. La luminance totale est pré-corrigée pour ne garder qu’une dépendance à la transmittance diffuse, à la contribution des aérosols et à la luminance marine.<br> <br> Le produit pré-corrigé et les angles de mesure sont assimilés à l’aide du code Self-Organizing Map NeuroVaria (SOM-NV) de Diouf et al. (2013). SOM-NV est un algorithme basé sur deux modèles statistiques qui permettent de classer un ensemble de données sur une carte, puis d’utiliser les informations de cette carte pour restituer les paramètres atmosphériques et océaniques de l’observation satellite.<br> <br> Les paramètres restitués sont les spectres de réflectance marine (Rrs(λ)) et l’épaisseur optique des aérosols (AOT) à 869 nm (aot_869). Les Rrs au bleu (443 et 488 nm) et au vert (547 nm) servent à calculer la concentration en chlorophylle-a à partir de l’algorithme OCx de OBPG (chl_ocx).<br> <br> Ces paramètres géophysiques sont projetés sur une grille fixe à 1/96° de résolution et archivés au format de fichiers netcdf journaliers. Chaque fichier netcdf contient cinq réflectances du visible Rrs(λ) (avec λ = 412, 443, 488, 531 et 547 nm), la chl_ocx, l’aot_869, et les coordonnées latitude et longitude. Ces paramètres sont décrits dans les fichiers, ainsi que les attributs globaux.</p> <p><br> Les fichiers netcdf sont formatés comme suite : SOM-NV-Ayyyydddhhmmss.nc ; avec yyyy = année ; ddd =<br> jour julien ; hh = heure ; mm = minute ; ss = seconde. L'extension "Ayyyydddhhmmss.nc", correspond au<br> nom du fichier MODIS_aqua du jour. Dans le cas où deux fichiers existent pour un même jour, à 5 minutes<br> près, les deux scans sont concaténés et l'orbite garde le nom du deuxième fichier.<br> Tous les fichiers sont compressés en interne à un niveau 4, pour faciliter le transfert.</p>
Labeled songs of domestic canary M1-2016-spring (Serinus canaria)
<p><strong>Labeled songs of domestic canary M1-2016-spring (Serinus canaria)</strong></p> <p><em>J. Giraudon*<sup>123</sup>, N. Trouvain*<sup>123</sup>, A. Cazala<sup>4</sup>, C. Del Negro<sup>4</sup>, X. Hinaut<sup>123</sup></em></p> <p><sup>1</sup> Inria Bordeaux Sud-Ouest, France</p> <p><sup>2</sup> LaBRI, Bordeaux INP, CNRS, UMR 5800, France</p> <p><sup>3</sup> Institut des Maladies Neurogégénératives, Université de Bordeaux, CNRS, UMR 5293, France</p> <p><sup>4 </sup>Paris-Saclay University, UMR 9197 CNRS, Paris-Saclay Institute of Neuroscience, France </p> <p><em>* these authors participated equally to this work.</em></p> <p><strong>General information</strong></p> <p>This dataset contains ~3h of labeled songs (459 songs) of one male canary (called M1) recorded between May 24th and June 15th 2016. Songs were recorded in a sound-isolation chamber using a RODE M3 microphone, an external sound card for microphone amplification (M-Audio Fast Track Ultra 8R), and the software Sound Analysis Pro 2011 (SAP). SAP parameters were set with conservative thresholds (software threshold to 4-6) in order to record the initiation of canary's songs which can be low in volume.</p> <p>Songs were hand labelled by one human expert using Audacity. They were then checked and corrected by another human expert assisted by an automated program based on recurrent neural networks (see References).</p> <p><strong>Dataset description</strong></p> <p>Canary songs are labeled using 27 different identified syllable classes + 1 "call" class identifying simple off-song calls + 1 "TRASH" class for irrelevant sounds (very rare vocalizations or non-bird sounds) + 1 "SIL" class for silence between vocalizations. Songs are annotated at the phrase level: a phrase consists of a repetition of a single syllable type and each phrase type is assigned a label.</p> <p>Annotations are provided in CSV format in the "M1-2016-spring_csv_annotations.zip" archive. There is one file per song, containing:</p> <ul> <li>a "wave" column indicating the song's audio filename;</li> <li>"start" and "end" columns indicating the temporal delimitation of the label from the begining of the song, in seconds;</li> <li>a "syll" column indicating the labels.</li> </ul> <p>Annotations are also provided in <a href="https://manual.audacityteam.org/man/importing_and_exporting_labels.html">Audacity TXT format</a> in the "M1-2016-spring_audacity_annotations.zip" archive. There is one file per song, containing three tabulation-separated columns. The first two column indicates the temporal delimitation (start and end) of the phrase from the begining of the song. The thrid one contains the associated label. Annotations filenames match corresponding song audio filename.</p> <p>Songs are provided in WAV format (44kHz sampling rate) in the "M1-2016-spring_audio.zip" archive. There is one file per song: audio filenames match corresponding annotation filenames.</p> <p><strong>References</strong></p> <p>This dataset was used in:</p> <p>N. Trouvain, X. Hinaut (2021) Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs. HAL preprint <a href="https://hal.inria.fr/hal-03203374">⟨hal-03203374⟩</a></p>
An interactive radiocarbon database for the Canary Islands
<p>The dataset described in this work represents the first open-access compilation of uncalibrated radiocarbon dates for the archaeology of Canary Islands</p>
FIG. 22. — A, B in The unknown bathyal of the Canaries: new species and new records of deep-sea Mollusca
FIG. 22. — A, B, Gymnobela abyssorum (Locard, 1897), shell from DW120 (10.5 mm); new to the Canaries; C, D, Kurtziella serga (Dall, 1881), shell from DW130 (7.7 mm); new to the Canaries; E, Kurtziella serga, shell from DW129 (8.8 mm); F, G, Famelica monotropis (Dautzenberg & H. Fischer, 1896), shell from DW130 (5.7 mm); new to Spanish waters; H-I, Neopleurotomoides callembryon (Dautzenberg & H. Fischer, 1896), shell from DW130 (2.3 mm); new to Spanish waters; J, Neopleurotomoides callembryon, scanning electron micrograph of the protoconch of another shell from DW130; K-L, Pleurotomella demosia (Dautzenberg & H. Fischer, 1896), shell from DW126 (8.7 mm); new to the Canaries; M-N, Pleurotomella eurybrocha (Dautzenberg & H. Fischer, 1896), shell from DW130 (3.8 mm); new to the Canaries. Scale bar: J, 500 µm, all measurements refer to shell height.
FIG. 25. — A-C in The unknown bathyal of the Canaries: new species and new records of deep-sea Mollusca
FIG. 25. — A-C, Spirolaxis lamellifer (Rehder, 1935), shell from DW120 (diameter 3.7 mm); new to the Canaries; D-F, Orbitestella pruinosa n. sp., holotype from DW130 (diameter 0.8 mm); G, Graphis gracilis (Monterosato, 1874), shell from DW130 (height 2.1 mm); H, I, Odostomia madeirensis Peñas, Rolán & Swinnen, 2014, shell from DW133 (height 2.2 mm); new to Spanish waters; J, K, Liostomia canaliculata n. sp., holotype from DW130 (height 1 mm); L, M, Ringicula pirulina Locard, 1897, shell from DW130 (6.4 mm); N, Colpodaspis pusilla M. Sars, 1870, shell from DW126 (1.4 mm); new to the Canaries.
FIG. 11. — A-C in The unknown bathyal of the Canaries: new species and new records of deep-sea Mollusca
FIG. 11. — A-C, Discaclis canariensis Moolenbeek & Warén, 1987, shell from DW133 (diameter 1.2 mm); D-J, Discaclis lamellata n. sp.: D-F, holotype (sh.) from DW130 (diameter 1.0 mm); G, paratype (sh.), same locality (diameter 0.95 mm); H, protoconch of another paratype; I, protoconch of another paratype in apical view; J, microsculpture on the shoulder, same shell as I. Scale bars: H, I, 100 µm; J, 20 µm.
FIG. 2. — A, B in The unknown bathyal of the Canaries: new species and new records of deep-sea Mollusca
FIG. 2. — A, B, Bathysciadium costulatum (Locard, 1898), shell from DW130 (2.3 mm length); new to Spanish waters; C, D, Copulabyssia corrugata (Jeffreys, 1883), shell from DW130 (1.6 mm length); new to the Canaries; E, F, Profundisepta profundi (Jeffreys, 1877), shell from DW130 (3.6 mm length); new to Spanish waters; G, H, Fissurisepta granulosa Jeffreys, 1883, shell from DW130 (2.3 mm length); new to the Canaries; I-J, Satondella danieli Segers, Swinnen & Abreu, 2009, shell from DW130 (1.8 mm maximum diameter); new to Spanish waters.
ERT data collected at the Corona volcano (Lanzarote, Canary Islands) during the European Space Agency (ESA) testing campaign PANGAEA-X 2017
<p>This dataset contains the ERT (Electrical Resistivity Tomography) data collected between 22 and 23 November 2017 at the Corona volcano (Lanzarote, Canary Islands, Fig. 1) for the detection of lava tubes and the stratigraphic investigation of planetary volcanic analogues. This geophysical survey was carried out within the European Space Agency (ESA) testing campaign PANGAEA-X 2017 (Bessone et al., 2018), aimed at integrating astronaut training-data collection, documentation, analogue field geology procedures with remote sensing and in situ geophysical methods. </p> <p>Two ERT profiles were acquired in NE-SW and NNE-SSW orientations (Fig. 1). These were located roughly orthogonal to the Corona lava tube system and as far as possible on top of the main lava tube axes. The longer profile, profile D, is 470 m in length and was obtained using 48 electrodes spaced 10 m apart. The profile orientation is from SW to NE (electrode 1 to 48). The profile was acquired to detect lava tubes in test site D (sub-area south) where the exact location of a lava tube was known thanks to a LiDAR TLS (Terrestrial Laser Scan) subsurface survey (Santagata et al., 2018). A shorter profile, profile E, is 235 m long and was obtained using 48 electrodes 5 m apart. The profile orientation is from SSW to NNE (electrode 1 to 48). This profile was acquired in test site E (sub-area north) to provide a more detailed investigation of the potential existence of inaccessible sections of the tube whose location could be indicated by the evidence of closely-spaced aligned collapse structures.</p> <p>Each profile was collected using measure sequences compounded by 276 Wenner-Schlumberger array quadrupoles which ensure high vertical resolution and signal amplitude and 328 dipole-dipole array quadrupoles which provide enhanced lateral resolution. A fully automatic multi-electrode resistivity meter SYSCAL Jr Switch-48 by IRIS Instruments (400 V max output voltage, 1200 mA max output current, 100 W max output power, <a href="http://www.iris-instruments.com/syscal-juniorsw.html">http://www.iris-instruments.com/syscal-juniorsw.html</a>), was used for data collection.</p> <p>At most of the measurement points, it was necessary to drill the basalt using a hand drilling machine in order to place the tips of the electrodes into the ground at a depth of approximately 40 cm. The electrodes also needed to kept moist to reduce contact resistance between the electrode and the ground. A large amount of water (up to 2 liters per point) was needed for profile D, situated in an area above the lava tubes with very porous dry soil cover.</p> <p>The dataset is presented as a spreadsheet format which has the "space" as separator and the ".txt" extension. The structure of such a file is the following one:</p> <p>#, El array, Spa1/4, Rho, Dev, M, Sp, Vp, In, Time, Spa5/12, M1/20</p> <p>- #: Data point number</p> <p>- El array: Electrode array</p> <p>- Spa. 1/4: four spacing parameters (corresponding to the electrode array – in m)</p> <p>- Rho: resistivity value (in Ohm.m)</p> <p>- Dev: standard deviation (quality factor, in %)</p> <p>- M: global chargeability value (induced polarization parameter (in mV/V – "=0" if only-resistivity data))</p> <p>- Sp: spontaneous polarization (measured just before the injection, in mV)</p> <p>- Vp: measured primary voltage (in mV)</p> <p>- In: injected current intensity (in mA)</p> <p>- Time: injection time (pulse duration, in s)</p> <p>- Spa. 5/8: other spacing parameters (in m)</p> <p>- Spa. 9/12: electrode elevation (in m)</p> <p>- M1/M20: partial chargeability values (induced polarization window (in mV/V – "=0" if only-resistivity data))</p> <p> </p> <p>Acknowledgements</p> <p>The authors are grateful to ESA and all PANGAEA-X 2017 staff, particularly Loredana Bessone, Matthias Maurer, Herve Stevenin and Igor Drozdovskiy for their participation in data collection during some of the experiments and to the MilesBeyond Team, particularly Francesco Maria Sauro for his logistical support. Regional and local remote sensing data were obtained by the Spanish Instituto Geográfico Nacional (https://www.ign.es) and Gobierno de Canarias (https://www.grafcan.es, <a href="https://opendata.sitcan.es/">https://opendata.sitcan.es</a>).</p> <p> </p> <p>References</p> <p>Bessone, L., et al., 2018, Testing technologies and operational concepts for field geology exploration of the Moon and beyond: the ESA PANGAEA-X campaign, Geophysical Research Abstract, #EGU2018-4013.</p> <p>Santagata, T., Sauro, F., Massironi, M., Pozzobon, R., Del Vecchio, U., Lazzaroni, M., Damiano, N., Tonello, M., Tomasi, I., Martínez-Frìas, J. and Mateo Medero, E., 2018. Subsurface laser scanning and photogrammetry in the Corona Lava Tube System, Lanzarote, Spain, EGU General Assembly 2018, pp. EGU2018-5290.</p>
Figure 3. Diplecogaster tonstricula n in Diplecogaster tonstricula, a new species of cleaning clingfish (Teleostei: Gobiesocidae) from the Canary Islands and Senegal, eastern Atlantic Ocean, with a review of the Diplecogaster-ctenocrypta species-group
Figure 3. Diplecogaster tonstricula n. sp., CCML uncat., paratype, specimen 1, 22.9 mm SL. Head lateral line system. (A) Dorsal view of head; (B) ventral view of head. Bar 1 mm.
Fig. 1 in Flower-visiting behaviour and habitats of the taxa of the Andrena wollastoni group (Hymenoptera, Anthophila, Micrandrena) on the Canary Islands compared to the Madeira Archipelago *
Fig. 1: (a) Typical crop-field margin with Hirschfeldia incana and Calendula arvensis, both frequently visited by Andrena catula (northern part of Gran Canaria, Zone IIb, 12th March 2018); photo: A. Schwabe. (b) Slope with ruderal vegetation (H. incana, frequently visited by A. g. gomerensis; additionally, Echium plantagineum and Psoralea bituminosa can be seen) with a grazed vegetation complex in the background (La Gomera, Zone IIb, 24th April 2016); photo: A. Schwabe. c: Road margin in the Teno area, with H. incana (frequently visited by A. a. tenoensis; additionally, E. plantagineum and Galactites tomentosus) (Tenerife, Zone IIA, 21st April 2016); photo: A. Schwabe. (d) A. a. tenoensis (female), collecting pollen on H. incana (margin of a small trail in the Teno area) (Tenerife, Zone IIA, 21st April 2016); photo: A. Schwabe.
Fig. 2 in Flower-visiting behaviour and habitats of the taxa of the Andrena wollastoni group (Hymenoptera, Anthophila, Micrandrena) on the Canary Islands compared to the Madeira Archipelago *
Fig. 2: (a) Habitat of the 'Cordillera Dorsal' species Descurainia lemsii, which is frequently visited by A. a. wildpreti (upper pine forest complex with rocky slopes, Zone III). Bottom right (not visited by A. a. wildpreti): Sideritis oroteneriffae ('Cordillera Dorsal' species); foreground: Adenocarpus viscosus (Tenerife, Montaña Ayosa; 22nd May 2019); photo: A. Schwabe. (b) Close-up of flowering and fruiting D. lemsii on a margin of rocky slopes in the Pinus canariensis forest complex (Tenerife, Montaña Ayosa; 26th May 2019); photo: A. Schwabe. (c) A. a. wildpreti (female, body length 7.7 mm); site and date of Fig. 2b; photo: A. Kratochwil. (d) Habitat of A. lineolata, visiting mainly D. bourgaeana (foreground) and Cytisus supranubius (white, background) (Tenerife, below Izaña, Teide area; Zone IV; 21st May 2019); photo: A. Schwabe.
Figure 2 in Parallel evolution in molar outline of murine rodents: the case of the extinct Malpaisomys insularis (Eastern Canary Islands)
Figure 2. Schematic representation of the modern and fossil murine rodents compared to Malpaisomys. Top, molecular phylogeny after Chevret (1994) and Chevret et al. (2001). A calibration of the time of divergence between taxa is given by reference to the divergence of the Rattus rattus lineage, estimated as having occurred 12 Mya (Chevret et al., 2001). The grey box includes the arvicanthine rodents, characterized by a herbivorous diet. Bottom, fossil lineages with investigated localities. Thick grey lines indicate taxa with stephanodont characteristics, thick black lines, complete stephanodonty. Crosses indicate extinct taxa.
Figure 1 in Amphi-Atlantic distribution of the Mancocumatinae (Cumacea: Bodotriidae), with description of a new genus dwelling in marine lava caves of Tenerife (Canary Islands)
Figure 1. Speleocuma guanche gen. et sp. nov. A, Ovigerous female, whole animal in lateral view. B, Adult male, whole animal in lateral view.
Figure 4 in Amphi-Atlantic distribution of the Mancocumatinae (Cumacea: Bodotriidae), with description of a new genus dwelling in marine lava caves of Tenerife (Canary Islands)
Figure 4. Speleocuma guanche gen. et sp. nov., ovigerous female. A, Right mandible. B, Pars incisa of the left mandible showing the lacinia mobilis. C, Maxillule. D, Maxilla. E, Maxilliped 1.
Figure 3 in Amphi-Atlantic distribution of the Mancocumatinae (Cumacea: Bodotriidae), with description of a new genus dwelling in marine lava caves of Tenerife (Canary Islands)
Figure 3. Speleocuma guanche gen. et sp. nov., ovigerous female A, Antenna 1. B, Maxilliped 2. C, Maxilliped 3. D, Pereopod 2. E, Pereopod 3. F, Pereopod 4. G, Last abdominal somite and uropod.
Figure 2 in Amphi-Atlantic distribution of the Mancocumatinae (Cumacea: Bodotriidae), with description of a new genus dwelling in marine lava caves of Tenerife (Canary Islands)
Figure 2. Speleocuma guanche gen. et sp. nov., preadult female, SEM micrographs. A, Anterior half of the carapace. B, Microstructure of the carapace showing the denticulate scales.
Figure 5 in Amphi-Atlantic distribution of the Mancocumatinae (Cumacea: Bodotriidae), with description of a new genus dwelling in marine lava caves of Tenerife (Canary Islands)
Figure 5. Speleocuma guanche gen. et sp. nov., adult male. A, Antennae 1 and 2. B, Mandible. C, Maxilula. D, Maxila. E, Maxilliped 2. F, Maxilliped 3. G, Pereopod 2. H, Pereopod 3. I, Pereopod 4. J, Pleopod. K, Uropod.
Figure 5 in Halacaridae (Acari) from Tenerife (Canary Islands)
Figure 5. Light-microscope images of halacarid species from Tenerife – A & B. Agaue adriatica (female) – Medial view of: tarsus I (A), telofemur I (B); C & D. Agauopsis tricuspis (male) – Medial view of: tarsus I (C), telofemur I (D); E–G. Halacarus actenos (male) – tarsus IV (E), integument (F), tip of gnathosoma (G); Rhombognathus procerus: H & J – female, I & K – male, ventral view of gnathosoma (H), genital openings (I, J, K).
Figure 9. Halacarus actenos Trouessart, 1889 in Halacaridae (Acari) from Tenerife (Canary Islands)
Figure 9. Halacarus actenos Trouessart, 1889 (male) – A. Dorsal view of idiosoma; B. Ventral view of idiosoma; C. Lateral view of palp; D. Chelicera; E. Medial view of leg I (Scale bars: A, B, E: 100 µm, C, D: 50 µm).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.